康复工程

可穿戴传感系统在上肢康复中应用的研究与实践

  • 王琦 ,
  • 陈炜 ,
  • Panos Markopoulos
展开
  • 1.荷兰埃因霍温理工大学工业设计系,埃因霍温 5612AJ;
    2.复旦大学电子工程系,上海市 200433;
    3.上海市医学图像处理与计算机辅助手术重点实验室,上海市 200433。
王琦(1988-),女,汉族,河北邯郸市人,博士研究生,主要研究方向:智能康复服装。

收稿日期: 2016-09-06

  网络出版日期: 2017-01-15

Application of Wearable Systems in Upper Extremity Rehabilitation: Research and Practice (review)

  • WANG Qi ,
  • CHEN Wei ,
  • Panos MARKOPOULOS
Expand
  • 1. Industrial Design Department of Eindhoven University of Technology, Eindhoven, 5612AP, the Netherlands;
    2. Center for Intelligent Medical Electronics (CIME), Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433, China;
    3. Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention, Shanghai 200433, China

Received date: 2016-09-06

  Online published: 2017-01-15

摘要

本文对可穿戴传感系统在上肢康复领域中的研究进行综述调研,根据论题相关的关键词搜到61篇文章,基于对文章摘要的初选和全文的筛选最终纳入18篇。这些文章可以分为三类:进行运动和姿势监测;提供终端用户反馈;整合交互游戏。基于现有文献的技术成熟度,临床证据的有效性和系统可用性等方面对其进行探讨,设计出一套智能康复服装系统,可用于多种病症康复。该系统包括一件整合了可穿戴电子元器件和智能织物的服装和基于安卓设备的反馈平台,可以实时通过衣服上的震动模块或来自手机的屏幕反馈、语音提示给予用户反馈。

本文引用格式

王琦 , 陈炜 , Panos Markopoulos . 可穿戴传感系统在上肢康复中应用的研究与实践[J]. 中国康复理论与实践, 2016 , 22(12) : 1462 -1461 . DOI: 10.3969/j.issn.1006-9771.2016.12.022

Abstract

This paper reported a structured literature survey of research in wearable technology for upper-extremity rehabilitation. A keyword based search returned 61 papers related to this topic. Examination of the abstracts of these papers identified 18 articles describing distinct wearable systems aimed at upper extremity rehabilitation. They were classified in three categories depending on their functionality: posture and motion monitoring; monitoring and feedback systems that supported rehabilitation exercises; serious games for rehabilitation training. We characterized the state of the art considering respectively the reported performance of these technologies, availability of clinical evidence, or known clinical applications. Based on the insights from the review study, we proposed a smart rehabilitation garment system for variety of patient groups. The garment integrated with smart textiles and wearable electronics. It presented real-time feedback as a vibration delivered through the garment, visual and audio instructions through Android-hand held device (smartphone or tablet).

参考文献

[1] Brochard S, Robertson J, Médée B, et al. What's new in new technologies for upper extremity rehabilitation? [J]. Curr Opin Neurol, 2010, 23(6): 683-687.
[2] Bonato P. Advances in wearable technology and applications in physical medicine and rehabilitation [J]. J Neurol Engineering Rehabil, 2005, 2(1): 2.
[3] Park S, Jayaraman S. Enhancing the quality of life through wearable technology [J]. IEEE Eng Med Biol Mag, 2003, 22(3): 41-48.
[4] Bonato P. Advances in wearable technology for rehabilitation [J]. Stud Health Technol Inform, 2009, 145: 145-159.
[5] Brewer BR, McDowell SK, Worthen-Chaudhari LC. Poststroke upper extremity rehabilitation: a review of robotic systems and clinical results [J]. Top Stroke Rehabil, 2014, 14(6): 22-44.
[6] Teng XF, Zhang YT, Poon CC, et al. Wearable medical systems for p-Health [J]. IEEE Rev Biomed Eng, 2008, 1: 62-74.
[7] Pantelopoulos A, Bourbakis NG. A survey on wearable sensor-based systems for health monitoring and prognosis [J]. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 2010, 40(1): 1-12.
[8] Wang Q, Chen W, Markopoulos P. Literature review on wearable systems in upper extremity rehabilitation [C]. 2014 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2014: 551-555.
[9] Nguyen KD, Chen IM, Luo Z, et al. A wearable sensing system for tracking and monitoring of functional arm movement [J]. IEEE/ASME Trans Mechatron, 2011, 16(2): 213-220.
[10] Lee GX, Low KS, Taher T. Unrestrained measurement of arm motion based on a wearable wireless sensor network [J]. IEEE Trans Instrum Meas, 2010, 59(5): 1309-1317.
[11] Daponte P, De Vito L, Sementa C. A wireless-based home rehabilitation system for monitoring 3D movements [C]. IEEE International Symposium, 2013: 282-287.
[12] Zhou H, Stone T, Hu H, et al. Use of multiple wearable inertial sensors in upper limb motion tracking [J]. Med Eng Phys, 2008, 30(1): 123-133.
[13] Brückner HP, Nowosielski R, Kluge H, et al. Mobile and wireless inertial sensor platform for motion capturing in stroke rehabilitation sessions [C]. 5th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI), 2013: 14-19.
[14] Pan JI, Chung HW, Huang JJ. Intelligent shoulder joint home-based self-rehabilitation monitoring system [J]. Int J Smart Home, 2013, 7(5): 395-404.
[15] Dunne L, Walsh P, Smyth B, et al. A system for wearable monitoring of seated posture in computer users [C]. 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007), 2007: 203-207.
[16] Patel S, Hughes R, Hester T, et al. A novel approach to monitor rehabilitation outcomes in stroke survivors using wearable technology [J]. Proc IEEE, 2010, 98: 450-461.
[17] Bento VF, Cruz VT, Ribeiro DD, et al. The vibratory stimulus as a neurorehabilitation tool for stroke patients: Proof of concept and tolerability test [J]. Neurol Rehabil, 2012, 30: 287-293.
[18] Markopoulos P, Timmermans AAA, Beursgens L, et al. Us'em: The user-centered design of a device for motivating stroke patients to use their impaired arm-hand in daily life activities [C]. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011: 5182-5187.
[19] Bleser G, Steffen D, Weber M, et al. A personalized exercise trainer for the elderly [J]. J Ambient Intell Smart Environ, 2013, 5: 547-562.
[20] Timmermans AAA, Seelen HAM, Geers RPJ, et al. Sensor-based arm skill training in chronic stroke patients: results on treatment outcome, patient motivation, and system usability [J]. IEEE Trans Neural Syst Rehabil Eng, 2010, 18(3): 284-292.
[21] Goodney A, Jung J, Needham S, et al. Dr. Droid: Assisting Stroke Rehabilitation Using Mobile Phones [M]// Mobile Computing, Applications, and Services. Springer Berlin Heidelberg, 2010, 76: 231-242.
[22] Mountain G, Wilson S, Eccleston C, et al. Developing and testing a telerehabilitation system for people following stroke: issues of usability [J]. J Eng Des, 2010: 223-236.
[23] Bonato P. Wearable sensors and systems [J]. IEEE Eng Med Biol Mag, 2010, 29: 25-36.
[24] Patel S, Park H, Bonato P, et al. A review of wearable sensors and systems with application in rehabilitation [J]. J Neurol Engineering Rehabil, 2012, 9: 21.
[25] Luo Z, Lim CK, Yang W, et al. An interactive therapy system for arm and hand rehabilitation [C]. IEEE Conference on Robotics, Automation and Mechatronics, 2010: 9-14.
[26] Alankus G, Lazar A, May M, et al. Towards customizable games for stroke rehabilitation [C]. CHI, 2010: 2113-2122.
[27] Beursgens L, Timmermans A, Markopoulos P. Playful ARM hand training after stroke [C]. CHI'12 Extended Abstracts on Human Factors in Computing Systems, 2012: 2399-2404.
[28] Chee KL, Chen IM, Luo ZQ, et al. A low cost wearable wireless sensing system for upper limb home rehabilitation [C]. IEEE Conference on Robotics, Automation and Mechatronics, 2010: 1-8.
[29] Wang Q, Toeters M, Chen W, et al. Zishi: a Smart Garment for Posture Monitoring [C]. CHI'12 Extended Abstracts on Human Factors in Computing Systems, 2016: 3792-3795.
文章导航

/